Determination of compressive strength using relevance vector machine and emotional neural network
Sign Up to like & getrecommendations! Published in 2019 at "Asian Journal of Civil Engineering"
DOI: 10.1007/s42107-019-00171-9
Abstract: Compressive strength is an important and pertinent property for the characterization of concrete. It is known that compressive strength of hardened concrete depends on the efficiency factor (K) of silica fume and its percentage replacement… read more here.
Keywords: compressive strength; relevance vector; neural network; vector machine ... See more keywords
Ensemble of relevance vector machines and boosted trees for electricity price forecasting
Sign Up to like & getrecommendations! Published in 2019 at "Applied Energy"
DOI: 10.1016/j.apenergy.2019.05.062
Abstract: Abstract Real-time prediction of electricity pricing signals is essential for scheduling load demand in price-directed grids. In a deregulated electricity market, this helps substantially increase the gains of utility companies and minimize the electricity cost… read more here.
Keywords: relevance vector; price forecasting; electricity; vector ... See more keywords
Stochastic seismic slope stability assessment using polynomial chaos expansions combined with relevance vector machine
Sign Up to like & getrecommendations! Published in 2021 at "Geoscience frontiers"
DOI: 10.1016/j.gsf.2020.03.016
Abstract: Abstract This paper presents probabilistic assessment of seismically-induced slope displacements considering uncertainties of seismic ground motions and soil properties. A stochastic ground motion model representing both the temporal and spectral non-stationarity of earthquake shakings and… read more here.
Keywords: slope; machine; relevance vector; vector machine ... See more keywords
Prediction and synthesis of novel layered double hydroxide with desired basal spacing based on relevance vector machine
Sign Up to like & getrecommendations! Published in 2017 at "Materials Research Bulletin"
DOI: 10.1016/j.materresbull.2017.03.045
Abstract: Abstract A Quantitative Structure Property Relationship (QSPR) model for the basal spacing of layered double hydroxide is developed in the present work by using generic algorithms feature selection, and relevance vector machine regression. The relative… read more here.
Keywords: layered double; basal spacing; relevance vector; double hydroxide ... See more keywords